The present disclosure provides a positioning method of a target node in a wireless ad hoc network, including: performing an initial positioning to obtain a first positioning result for the target node; determining, based on the first positioning result and a second positioning result for an other node in the wireless ad hoc network, whether a positioning error exists in the first positioning result or not, wherein the second positioning result at least contains an accurate second positioning result; and calculating a third positioning result for the target node based on the accurate second positioning result, in response to determining a positioning error exists in the first positioning result. The present disclosure further provides a positioning apparatus of a target node in a wireless ad hoc network, an electronic device, and a storage medium.
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4. The positioning method of claim 2, wherein the calculating a third positioning result comprises: calculating the third positioning result by using a trilateration method or a maximum likelihood method.
This invention relates to positioning methods, specifically improving accuracy in determining the location of a device using multiple positioning techniques. The problem addressed is the inherent inaccuracies in standalone positioning methods, such as those relying on signal measurements from satellites, base stations, or other reference points. These methods often suffer from errors due to environmental factors, signal interference, or limited reference points, leading to unreliable positioning results. The invention describes a method that combines multiple positioning techniques to enhance accuracy. Initially, a first positioning result is obtained using a first positioning method, such as satellite-based positioning (e.g., GPS). A second positioning result is then obtained using a second positioning method, such as base station-based positioning (e.g., cellular triangulation). These results are then refined by calculating a third positioning result using either a trilateration method or a maximum likelihood method. Trilateration involves determining the position based on the intersection of multiple distance measurements from known reference points, while the maximum likelihood method estimates the most probable position by minimizing errors in the observed data. The combined approach reduces errors and improves the reliability of the final position estimate. This method is particularly useful in applications requiring high-precision positioning, such as navigation systems, asset tracking, and autonomous vehicles.
5. The positioning method of claim 2, wherein the measuring a first distance comprises: measuring the first distance by using a received signal strength indication method.
This invention relates to positioning methods, specifically for determining the location of a device within a network. The problem addressed is accurately measuring distances between devices in a network to enable precise positioning, particularly in environments where traditional methods like GPS may be unreliable or unavailable. The method involves measuring a first distance between a first device and a second device using a received signal strength indication (RSSI) method. RSSI is a technique that estimates distance based on the strength of a received signal, where signal strength typically decreases with distance. The first device transmits a signal, and the second device measures the signal strength to determine the distance between them. This distance measurement is then used to calculate the position of the first device relative to the second device or other reference points in the network. The method may also involve measuring a second distance between the first device and a third device, where the second distance is measured using a different technique, such as time of flight (ToF) or angle of arrival (AoA). By combining multiple distance measurements from different devices and techniques, the method improves positioning accuracy. The positioning may be further refined by adjusting the measured distances based on environmental factors, such as obstacles or interference, to enhance reliability. The method is particularly useful in indoor or urban environments where signal propagation is complex.
6. The positioning method of claim 2, wherein the cumulative hop distance is propagated by the other node using a distance vector routing method.
This invention relates to wireless communication networks, specifically to a positioning method for determining the location of nodes within the network. The problem addressed is the challenge of accurately estimating node positions in environments where direct distance measurements are unreliable or unavailable, such as in multi-hop wireless networks. The method involves calculating a cumulative hop distance between nodes, where each hop represents a wireless communication link. The cumulative hop distance is propagated through the network using a distance vector routing protocol, which allows nodes to exchange and update distance information with neighboring nodes. This propagation ensures that each node can determine its position relative to other nodes based on the accumulated hop distances. The distance vector routing method involves each node maintaining a table of distances to other nodes, which is periodically updated as new information is received. By sharing these distance tables, nodes can collectively refine their position estimates. This approach improves positioning accuracy in dynamic or sparse networks where traditional methods like GPS or trilateration may fail. The method is particularly useful in scenarios where nodes are mobile or where direct line-of-sight measurements are obstructed. By leveraging the existing routing infrastructure, the solution provides a scalable and efficient way to estimate node positions without requiring additional hardware or complex computations.
13. A non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, causes the processor to implement the method of claim 1.
This invention relates to a computer program stored on a non-transitory computer-readable storage medium, designed to execute a method for processing data. The method involves receiving a first set of data from a first source and a second set of data from a second source. The system then processes these data sets to generate a combined output. The processing includes analyzing the first set of data to identify a first set of features and analyzing the second set of data to identify a second set of features. The system then compares the first set of features with the second set of features to determine a similarity score. Based on this score, the system generates a combined output that integrates the relevant aspects of both data sets. The method may also include filtering the data sets to remove irrelevant or redundant information before analysis. The combined output can be used for various applications, such as data fusion, decision-making, or predictive modeling. The invention addresses the challenge of effectively integrating disparate data sources to improve accuracy and reliability in data-driven systems. The computer program ensures that the method is executed efficiently and reliably on a computing device.
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May 13, 2020
November 15, 2022
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